Introduction to Operations Research, Volume 1CD-ROM contains: Student version of MPL Modeling System and its solver CPLEX -- MPL tutorial -- Examples from the text modeled in MPL -- Examples from the text modeled in LINGO/LINDO -- Tutorial software -- Excel add-ins: TreePlan, SensIt, RiskSim, and Premium Solver -- Excel spreadsheet formulations and templates. |
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Page 225
... given information to identify the optimal solution . ( b ) Use the given information to identify the shadow prices for the three resources . Z ( 0 ) 1 1 1 0 X2 ( 1 ) 0 1 I 5.2-2 . * Work through the revised simplex method step by step ...
... given information to identify the optimal solution . ( b ) Use the given information to identify the shadow prices for the three resources . Z ( 0 ) 1 1 1 0 X2 ( 1 ) 0 1 I 5.2-2 . * Work through the revised simplex method step by step ...
Page 760
... given the finding of the seismic survey . Prior Probabilities P ( state ) 0.25 Oil Conditional Probabilities Joint ... given FSS 0.6 FSS , given Oil 0.4 USS , given Oil 0.25 ( 0.4 ) = 0.1 Oil and USS 0.1 = 0.14 0.7 Oil , given USS 0.2 ...
... given the finding of the seismic survey . Prior Probabilities P ( state ) 0.25 Oil Conditional Probabilities Joint ... given FSS 0.6 FSS , given Oil 0.4 USS , given Oil 0.25 ( 0.4 ) = 0.1 Oil and USS 0.1 = 0.14 0.7 Oil , given USS 0.2 ...
Page 999
... given by 5 ( D − y ) . The probability density function for D is given by ¿ ( § ) = e . The holding cost when y exceeds D is given by y - D. A monthly discount factor of 0.95 is used . - T 19.7-7 . Solve the inventory problem given in ...
... given by 5 ( D − y ) . The probability density function for D is given by ¿ ( § ) = e . The holding cost when y exceeds D is given by y - D. A monthly discount factor of 0.95 is used . - T 19.7-7 . Solve the inventory problem given in ...
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Introduction to Operations Research Frederick S. Hillier,Gerald J. Lieberman No preview available - 2001 |
Common terms and phrases
activity algebraic algorithm allowable range artificial variables b₂ basic solution c₁ c₂ changes coefficients column Consider the following cost CPF solution CPLEX decision variables described dual problem dynamic programming entering basic variable example feasible region feasible solutions final simplex tableau final tableau following problem formulation functional constraints Gaussian elimination given goal goal programming graphical identify increase initial BF solution integer interior-point iteration leaving basic variable linear programming model linear programming problem LINGO LP relaxation lution Maximize Z maximum flow problem Minimize needed node nonbasic variables nonnegativity constraints objective function obtained optimal solution optimality test parameters path plant presented in Sec primal problem Prob procedure range to stay right-hand sides sensitivity analysis shadow prices shown simplex method slack variables solve the model Solver spreadsheet step subproblem surplus variables Table tion values weeks Wyndor Glass x₁ zero